Hospital-Based Medicine

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Latest AI and machine learning research in intensivists for healthcare professionals.

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Explainable Artificial Intelligence Helps in Understanding the Effect of Fibronectin on Survival of Sepsis.

Fibronectin (FN) plays an essential role in the host's response to infection. In previous studies, a...

Comparative Convolutional Dynamic Multi-Attention Recommendation Model.

Recently, an attention mechanism has been used to help recommender systems grasp user interests more...

Predictions on multi-class terminal ballistics datasets using conditional Generative Adversarial Networks.

Ballistic impacts are a primary risk in both civil and military defence applications, where successf...

A new fuzzy rule based multi-objective optimization method for cross-scale injection molding of protein electrophoresis microfluidic chips.

Injection molding is one of the most promising technologies for the large-scale production and appli...

Prediction algorithm for ICU mortality and length of stay using machine learning.

Machine learning can predict outcomes and determine variables contributing to precise prediction, an...

A Two-Stream Graph Convolutional Network Based on Brain Connectivity for Anesthetized States Analysis.

Investigating neural mechanisms of anesthesia process and developing efficient anesthetized state de...

Evaluating Ensemble Learning Methods for Multi-Modal Emotion Recognition Using Sensor Data Fusion.

Automatic recognition of human emotions is not a trivial process. There are many factors affecting e...

Towards in vivo ground truth susceptibility for single-orientation deep learning QSM: A multi-orientation gradient-echo MRI dataset.

Recently, deep neural networks have shown great potential for solving dipole inversion of quantitati...

An Efficient Multi-Scale Convolutional Neural Network Based Multi-Class Brain MRI Classification for SaMD.

A brain tumor is the growth of abnormal cells in certain brain tissues with a high mortality rate; t...

A Highly Multi-Stable Meta-Structure via Anisotropy for Large and Reversible Shape Transformation.

Shape transformation offers the possibility of realizing devices whose 3D shape can be altered to ad...

Factors driving provider adoption of the TREWS machine learning-based early warning system and its effects on sepsis treatment timing.

Machine learning-based clinical decision support tools for sepsis create opportunities to identify a...

Regularization Meets Enhanced Multi-Stage Fusion Features: Making CNN More Robust against White-Box Adversarial Attacks.

Regularization has become an important method in adversarial defense. However, the existing regulari...

Multi-task deep learning for glaucoma detection from color fundus images.

Glaucoma is an eye condition that leads to loss of vision and blindness if not diagnosed in time. Di...

Machine learning for multi-parametric breast MRI: radiomics-based approaches for lesion classification.

In the artificial intelligence era, machine learning (ML) techniques have gained more and more impor...

Multi-Agent Team Learning in Virtualized Open Radio Access Networks (O-RAN).

Starting from the concept of the Cloud Radio Access Network (C-RAN), continuing with the virtual Rad...

Protocol to predict mechanical properties of multi-element ceramics using machine learning.

Identifying and designing high-performance multi-element ceramics based on trial-and-error approache...

A Novel Efficient Convolutional Neural Algorithm for Multi-Category Aliasing Hardware Recognition.

When performing robotic automatic sorting and assembly operations of multi-category hardware, there ...

Classification of multi-lead ECG with deep residual convolutional neural networks.

. Automatic electrocardiogram (ECG) interpretation based on deep learning methods is attracting incr...

Multi-mask self-supervised learning for physics-guided neural networks in highly accelerated magnetic resonance imaging.

Self-supervised learning has shown great promise because of its ability to train deep learning (DL) ...

A multi-birth metric learning framework based on binary constraints.

Multi-metric learning plays a significant role in improving the generalization of algorithms related...

QMEDNet: A quaternion-based multi-order differential encoder-decoder model for 3D human motion prediction.

In order to deal with the sequence information in the task of 3D human motion prediction effectively...

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